Title | ||
---|---|---|
Unsupervised manifold learning through reciprocal kNN graph and Connected Components for image retrieval tasks. |
Abstract | ||
---|---|---|
•Presentation of an unsupervised manifold learning method based on Reciprocal kNN Graphs and Connected Components.•Discussion about the use of the method for distance learning in order to improve the effectiveness of image retrieval tasks.•Discussion about contributions, algorithm’s efficiency and progresses in front of other unsupervised approaches.•Experimental evaluation considering various datasets, several features and comparison with state-of-the-art methods. |
Year | DOI | Venue |
---|---|---|
2018 | 10.1016/j.patcog.2017.05.009 | Pattern Recognition |
Keywords | Field | DocType |
Content-based image retrieval,Unsupervised manifold learning,Reciprocal kNN graph,Connected components | Reciprocal,Pattern recognition,Computer science,Image retrieval,Manifold alignment,Artificial intelligence,Connected component,Nonlinear dimensionality reduction,Manifold,Content-based image retrieval,Machine learning,Visual Word | Journal |
Volume | Issue | ISSN |
75 | C | 0031-3203 |
Citations | PageRank | References |
9 | 0.47 | 61 |
Authors | ||
3 |
Name | Order | Citations | PageRank |
---|---|---|---|
Daniel Carlos Guimarães Pedronette | 1 | 304 | 25.47 |
Filipe Marcel Fernandes Gonçalves | 2 | 9 | 0.47 |
Ivan Rizzo Guilherme | 3 | 26 | 6.70 |